Associative Classifiers for Medical Images

  • Maria-Luiza Antonie
  • Osmar R. Zaïane
  • Alexandru Coman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2797)

Abstract

This paper presents two classification systems for medical images based on association rule mining. The system we propose consists of: a pre-processing phase, a phase for mining the resulted transactional database, and a final phase to organize the resulted association rules in a classification model. The experimental results show that the method performs well, reaching over 80% in accuracy. Moreover, this paper illustrates how important the data cleaning phase is in building an accurate data mining architecture for image classification.

Keywords

Medical Image Association Rule Pruning Technique Apriori Algorithm Digital Mammogram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Maria-Luiza Antonie
    • 1
  • Osmar R. Zaïane
    • 1
  • Alexandru Coman
    • 1
  1. 1.Department of Computing ScienceUniversity of AlbertaEdmontonCanada

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